{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "中文"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "微博搜索\n",
    "https://s.weibo.com/weibo?q=%E6%AD%A6%E6%B1%89&xsort=hot&suball=1&timescope=custom:2020-01-01:&Refer=g\n",
    "\n",
    "然后打开Console\n",
    "document.querySelectorAll('.content .txt').forEach(function(div){\n",
    "    console.log(div.innerText)\n",
    "    txtl.push(div.innerText)})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "txt=''' 【捐了那么多东西怎么还缺？#记者探访武汉市红十字会# 】总台央广记者31日来到位于湖北省武汉市胜利街162号的武汉市红十字会。因红十字会已成为舆论焦点，采访时记者明显感受到现场工作人员的压力和对媒体的防备。记者始终没有在现场见到红十字会的工作人员，一位从其他部门抽调来的工作人员私下说，“ ​ \n",
    " \n",
    "                    【捐了那么多东西怎么还缺？#记者探访武汉市红十字会# 】总台央广记者31日来到位于湖北省武汉市胜利街162号的武汉市红十字会。因红十字会已成为舆论焦点，采访时记者明显感受到现场工作人员的压力和对媒体的防备。记者始终没有在现场见到红十字会的工作人员，一位从其他部门抽调来的工作人员私下说，“红十字会几十年没打大仗了，一打仗就有点乱。”  #总台记者探访武汉红十字会# 详情>>O捐了那么多东西怎么还缺？记者探访武汉市红十字会 \n",
    "                \n",
    " 【#9省物资直达武汉协和# 快递司机：水都不敢多喝，怕耽误时间】截至1日上午10时15分，北京、山东、黑龙江、湖南、海南、甘肃、四川、内蒙古、辽宁等9省（区、市）40个单位将援助物资直接运抵协和医院。包括医用口罩、医用手套、隔离衣、防护服、防护眼镜、一次性鞋套和工作帽等总计30多万件。 ​\n",
    " 【究竟是物资紧缺还是物资分配环节存在问题？看着揪心】网友@BigWayneWu ： 物资紧缺，大战当前，武汉协和医院西区的一线老师们没有条件创造条件也要上，泪目 ​\n",
    " 【#武汉小姐姐每天给医院做饭800份#】武汉盘龙城一家餐厅，专门为金银潭等医院的医护人员做盒饭。由于忙不过来，店主小姐姐还叫上父母兄妹齐上阵，每天能制作盒饭800-1000份。小姐姐说：“看到医护人员的朋友圈，很受不了，我想做这个事儿。”加话题#武汉日记#发微博，在昵称后点亮icon，一起为武 ​ \n",
    " \n",
    "                    【#武汉小姐姐每天给医院做饭800份#】武汉盘龙城一家餐厅，专门为金银潭等医院的医护人员做盒饭。由于忙不过来，店主小姐姐还叫上父母兄妹齐上阵，每天能制作盒饭800-1000份。小姐姐说：“看到医护人员的朋友圈，很受不了，我想做这个事儿。”加话题#武汉日记#发微博，在昵称后点亮icon，一起为武汉加油！（总台央视记者张竣 单泽）#央视记者武汉vlog# L央视新闻的微博视频 \n",
    "                \n",
    " 【终于！#武汉协和医院收到急需物资#】今天下午，武汉协和医院急需的一批医疗物资已经送到医生和护士手里。这批物资由武大和华科校友会联合捐赠，包括超过20万个医疗口罩，以及外罩和手套等个人防护装备。希望更多物资能尽快到达一线！（沈文敏） ​\n",
    " #共同战疫#【直播！总台#央视记者采访武汉协和医院#！】口罩等应急物资是否短缺？医院物资来源有哪些？发放有何标准？记者独家专访华中科技大学附属协和医院党委副书记孙晖，回应各方关切。看直播，关注！(总台央视记者王宇) 央视新闻的微博直播 . ​\n",
    " 【捐了那么多东西怎么还缺？#总台记者探访武汉红十字会#】记者看到，原来的展馆被临时征用为武汉市红十字会存放捐赠物资的仓库。展馆的一个角落被改造为办公室，有工作人员在登记造册，地上堆放着货物。武汉市常务副市长胡亚波说：“大量捐赠物资都是民用的。很多有用的东西，现在特别紧缺。一方面需要 ​ \n",
    " \n",
    "                    【捐了那么多东西怎么还缺？#总台记者探访武汉红十字会#】记者看到，原来的展馆被临时征用为武汉市红十字会存放捐赠物资的仓库。展馆的一个角落被改造为办公室，有工作人员在登记造册，地上堆放着货物。武汉市常务副市长胡亚波说：“大量捐赠物资都是民用的。很多有用的东西，现在特别紧缺。一方面需要的东西进不来，另一方面医护人员不需要的东西堆积如山。”详情↓ O捐了那么多东西怎么还缺？ 总台记者探访武汉市红十字会 \n",
    "                \n",
    " 【#滞留海外湖北籍同胞回国瞬间#】31日，两驾包机返回武汉，滞留海外的湖北籍同胞顺利回国。抵达机场那一刻，他们说：“回家，真好！”L人民日报的微博视频 ​\n",
    " #新型冠状病毒感染肺炎#【上海药物所、武汉病毒所联合发现中成药双黄连口服液可抑制新型冠状病毒】记者31日从中国科学院上海药物所获悉，该所和武汉病毒所联合研究初步发现，中成药双黄连口服液可抑制新型冠状病毒。此前，上海药物所启动由蒋华良院士牵头的抗新型冠状病毒感染肺炎药物研究应急攻关团队 ​ \n",
    " \n",
    "                    #新型冠状病毒感染肺炎#【上海药物所、武汉病毒所联合发现中成药双黄连口服液可抑制新型冠状病毒】记者31日从中国科学院上海药物所获悉，该所和武汉病毒所联合研究初步发现，中成药双黄连口服液可抑制新型冠状病毒。此前，上海药物所启动由蒋华良院士牵头的抗新型冠状病毒感染肺炎药物研究应急攻关团队，在前期SARS相关研究和药物发现成果基础上，聚焦针对该病毒的治疗候选新药筛选、评价和老药新用研究。双黄连口服液由金银花、黄芩、连翘三味中药组成。中医认为，这三味中药具有清热解毒、表里双清的作用。现代医学研究认为，双黄连口服液具有广谱抗病毒、抑菌、提高机体免疫功能的作用，是目前有效的广谱抗病毒药物之一。上海药物所长期从事抗病毒药物研究，2003年“非典”期间，上海药物所左建平团队率先证实双黄连口服液具有抗SARS冠状病毒作用,十余年来又陆续证实双黄连口服液对流感病毒（H7N9、H1N1、H5N1）、严重急性呼吸综合征冠状病毒、中东呼吸综合征冠状病毒具有明显的抗病毒效应。目前，双黄连口服液已在上海公共卫生临床中心、华中科技大学附属同济医院开展临床研究。（记者董瑞丰）（完） \n",
    "                \n",
    " 【上海药物所、武汉病毒所联合发现：#双黄连可抑制新型冠状病毒#】31日从中国科学院上海药物所获悉，该所和武汉病毒所联合研究初步发现，中成药#双黄连口服液可抑制新型冠状病毒#。此前，上海药物所启动由蒋华良院士牵头的抗新型冠状病毒感染肺炎药物研究应急攻关团队，在前期SARS相关研究和药物发现成 ​ \n",
    " \n",
    "                    【上海药物所、武汉病毒所联合发现：#双黄连可抑制新型冠状病毒#】31日从中国科学院上海药物所获悉，该所和武汉病毒所联合研究初步发现，中成药#双黄连口服液可抑制新型冠状病毒#。此前，上海药物所启动由蒋华良院士牵头的抗新型冠状病毒感染肺炎药物研究应急攻关团队，在前期SARS相关研究和药物发现成果基础上，聚焦针对该病毒的治疗候选新药筛选、评价和老药新用研究。双黄连口服液由金银花、黄芩、连翘三味中药组成。中医认为，这三味中药具有清热解毒、表里双清的作用。现代医学研究认为，双黄连口服液具有广谱抗病毒、抑菌、提高机体免疫功能的作用，是目前有效的广谱抗病毒药物之一。上海药物所长期从事抗病毒药物研究，2003年“非典”期间，上海药物所左建平团队率先证实双黄连口服液具有抗SARS冠状病毒作用,十余年来又陆续证实双黄连口服液对流感病毒（H7N9、H1N1、H5N1）、严重急性呼吸综合征冠状病毒、中东呼吸综合征冠状病毒具有明显的抗病毒效应。目前，双黄连口服液已在上海公共卫生临床中心、华中科技大学附属同济医院开展临床研究。（新华社） \n",
    "                \n",
    " 【湖北红十字会工作人员回应物资分配：#凭什么医院要分三六等级#】这位工作人员表示，捐赠物资是宏观调控，是一个从前到后的整体规划，有时候这个人多，有时候那个人多，不是很正常的现象吗？他们（武汉仁爱医院和天佑医院）也是医院，是中华人民共和国为人民群众看病、救命的医院，凭什么医院要分三六 ​ \n",
    " \n",
    "                    【湖北红十字会工作人员回应物资分配：#凭什么医院要分三六等级#】这位工作人员表示，捐赠物资是宏观调控，是一个从前到后的整体规划，有时候这个人多，有时候那个人多，不是很正常的现象吗？他们（武汉仁爱医院和天佑医院）也是医院，是中华人民共和国为人民群众看病、救命的医院，凭什么医院要分三六等级？凭什么不能给这些医院发口罩？都是医生都是人命，都在接受肺炎的病人，凭什么不能捐？#抗击肺疫最前线##武汉新型冠状病毒感染肺炎防控专题# O湖北省疫情防控指挥部：非定向捐赠物资分配方案由红十字会自行拟定 2北京·安贞西里二区 2北京·安贞西里二区 \n",
    "                \n",
    " 【正在直播：#探访武汉雷神山医院施工现场#】湖北武汉，雷神山医院进入建设倒计时。@人民日报 记者来到工地实地探访！戳直播↓↓ 人民日报的微博直播 . ​\n",
    " 【#捐了那么多东西为啥还缺#？记者实地探访武汉红十字会】爱心捐赠总量大可为何总是不够用？武汉市常务副市长胡亚波表示：①现场有些货物不是我们要的，有些货装得不规范；②医院一方面需要的东西进不来，另一方面医护人员不需要的东西堆积如山。医护人员不能用的口罩民众可以戴，后续会下发社区等；③ ​ \n",
    " \n",
    "                    【#捐了那么多东西为啥还缺#？记者实地探访武汉红十字会】爱心捐赠总量大可为何总是不够用？武汉市常务副市长胡亚波表示：①现场有些货物不是我们要的，有些货装得不规范；②医院一方面需要的东西进不来，另一方面医护人员不需要的东西堆积如山。医护人员不能用的口罩民众可以戴，后续会下发社区等；③科学调配是一个最复杂的系统工程，涉及到了方方面面，我们的力量还是不够。详戳↓↓L中国之声的微博视频 \n",
    "                \n",
    " 【#你好，明天#】武汉市委书记称：将责成慈善机构每三天发布捐赠物品去向。疫情仍在尖峰时刻，一线医护渴求物资，一只口罩可能就是一条命。物资调配必须遵循谁最急需、谁来使用的原则，绝不能耽搁拖延，更不能变糊涂账。歌手韩红说得好：一包方便面都可公示。公平高效调配捐赠物，以公开赢得公信。 ​\n",
    " 【武汉医生：1/4同事被感染 口罩不合格也按时进病房】“1月31日，最新通知下来了，由于医护人员减员情况严重，医院决定每个科室留5名医生倒班，每班6小时；这样的值班时长对于已连续奋战10天的医护人员来说危险系数很高↓↓医生称他连续10天没有离开医院，目前病房爆满，已经出现医护人员交叉感染 ​ \n",
    " \n",
    "                    【武汉医生：1/4同事被感染 口罩不合格也按时进病房】“1月31日，最新通知下来了，由于医护人员减员情况严重，医院决定每个科室留5名医生倒班，每班6小时；这样的值班时长对于已连续奋战10天的医护人员来说危险系数很高↓↓医生称他连续10天没有离开医院，目前病房爆满，已经出现医护人员交叉感染↓↓更多细节↓↓O武汉医生:1/4同事被感染 口罩不合格也要进病房 \n",
    "                \n",
    " 【武汉封城后，有些事只有外卖小哥知道】\n",
    "\n",
    "在现在武汉空空荡荡的城市街道上，外卖小哥和快递员是最繁忙的人。在这个特殊时期，他们也见证了世间百态：陌生市民为前线医生点大餐；一个顾客点了餐，备注鸡蛋要生的，因为家里没有余粮了；留在家中的猫咪产仔了，结果因为主人不在，新生的小猫宝宝都死了… ​ \n",
    " \n",
    "                    【武汉封城后，有些事只有外卖小哥知道】在现在武汉空空荡荡的城市街道上，外卖小哥和快递员是最繁忙的人。在这个特殊时期，他们也见证了世间百态：陌生市民为前线医生点大餐；一个顾客点了餐，备注鸡蛋要生的，因为家里没有余粮了；留在家中的猫咪产仔了，结果因为主人不在，新生的小猫宝宝都死了……为此，《Vista看天下》采访了这个春节一直奔波在武汉街头的几位外卖小哥和快递小哥……本文系Vista看天下APP独家稿件，未经允许请勿转载。 \n",
    "                \n",
    " 【武汉市委书记：我现在是一种内疚愧疚自责的心态】1月31日21：35，央视新闻频道《新闻1+1》，主持人白岩松将连线湖北省委副书记、武汉市委书记马国强，解读公众关心的疫情问题。\n",
    "武汉市市委书记马国强：我现在是一种内疚、愧疚、自责的心态，如果早采取严厉的管控措施，结果会比现在好，对全国各地的 ​ \n",
    " \n",
    "                    【武汉市委书记：我现在是一种内疚愧疚自责的心态】1月31日21：35，央视新闻频道《新闻1+1》，主持人白岩松将连线湖北省委副书记、武汉市委书记马国强，解读公众关心的疫情问题。武汉市市委书记马国强：我现在是一种内疚、愧疚、自责的心态，如果早采取严厉的管控措施，结果会比现在好，对全国各地的影响要小，也会让党中央、国务院少操心。（央视）#白岩松对话湖北省委副书记# L视频-新闻1+1：武汉市市委书记马国强-我现在是一种内疚愧疚自责的心态 \n",
    "                \n",
    " 【莆田系医院获赠1.8万个口罩遭质疑，涉事医院院长：我们真的需要】30日，湖北省红十字会官网公布了17项捐赠物资的使用情况，其中莆田系医院武汉仁爱医院收到1.8万个KN95口罩，而防疫一线医院武汉协和医院仅收到3000个口罩，这让武汉仁爱医院陷入舆论漩涡。\n",
    "对此，武汉仁爱医院院长熊怡祥回应：武汉是 ​ \n",
    " \n",
    "                    【莆田系医院获赠1.8万个口罩遭质疑，涉事医院院长：我们真的需要】30日，湖北省红十字会官网公布了17项捐赠物资的使用情况，其中莆田系医院武汉仁爱医院收到1.8万个KN95口罩，而防疫一线医院武汉协和医院仅收到3000个口罩，这让武汉仁爱医院陷入舆论漩涡。对此，武汉仁爱医院院长熊怡祥回应：武汉是疫区，医院是危险的地方，我们真的需要口罩，但我们买不到口罩。1月22日，我们向社会求口罩，可是没求来。1月24日，向武汉市红十字会求援，没结果。1月26日，再向湖北省红十字会求援。1月27日，湖北省红十字会给了我们1.8万个KN95口罩。对于公众的质疑，院长称：我们医院确实是莆田系医院，莆田系备受争议，但不是所有莆田系医院都是坏的，我们医院有20年历史了。 \n",
    "                \n",
    " 【泪目！妈妈#给上前线军医儿子录制鼓励视频#：“盼望你早日平安归来”】“儿子，当妈妈知道的时候，你已经踏上征途，面对疫情挺身而出责无旁贷。虽然有点担心，但是妈妈坚决支持你。”大年三十晚上，空军军医大学医生史庆辉接到驰援武汉的命令。而这天，他的母亲刚刚出院回家。白衣战士们，我们都在等 ​ \n",
    " \n",
    "                    【泪目！妈妈#给上前线军医儿子录制鼓励视频#：“盼望你早日平安归来”】“儿子，当妈妈知道的时候，你已经踏上征途，面对疫情挺身而出责无旁贷。虽然有点担心，但是妈妈坚决支持你。”大年三十晚上，空军军医大学医生史庆辉接到驰援武汉的命令。而这天，他的母亲刚刚出院回家。白衣战士们，我们都在等你平安归来！  L人民日报的微博视频 \n",
    "                \n",
    " #请勿抢购自行服用双黄连口服液#【投票：#你买双黄连口服液了吗#？】31日新华社记者从中国科学院上海药物所获悉，该所和武汉病毒所联合研究初步发现，中成药双黄连口服液可抑制新型冠状病毒。目前该发现仍是初步研究，该药已在上海公共卫生临床中心、华中科技大学附属同济医院开展临床研究，对病人如何 ​ \n",
    " \n",
    "                    #请勿抢购自行服用双黄连口服液#【投票：#你买双黄连口服液了吗#？】31日新华社记者从中国科学院上海药物所获悉，该所和武汉病毒所联合研究初步发现，中成药双黄连口服液可抑制新型冠状病毒。目前该发现仍是初步研究，该药已在上海公共卫生临床中心、华中科技大学附属同济医院开展临床研究，对病人如何有效还要做大量的实验。特别提醒：按照@世界卫生组织 ，到目前为止，还没有用于预防和治疗新型冠状病毒的药物。特定的治疗方法正在研究中，并将通过临床试验进行测试。 你买双黄连口服液了吗？ \n",
    "                \n",
    "undefined'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "import jieba\n",
    "jieba.enable_parallel(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "import jieba.analyse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "from wordcloud import WordCloud, ImageColorGenerator\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "seg_list = jieba.cut(txt, cut_all=True)\n",
    "liststr = \" \".join(seg_list)\n",
    "# liststr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "总词数： 809\n"
     ]
    }
   ],
   "source": [
    "words = []\n",
    "for sen in txt.split():\n",
    "    words.extend(jieba.analyse.extract_tags(sen))\n",
    "print(\"总词数：\", len(words))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<wordcloud.wordcloud.WordCloud at 0x7f574b6a3e48>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wc=WordCloud(font_path=font_path, width=1000, height=860,)\n",
    "data=' '.join(words)\n",
    "wc.generate(data)\n",
    "wc.to_file('wc2.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/usr/share/fonts/truetype/wqy/wqy-microhei.ttc: WenQuanYi Micro Hei,文泉驛微米黑,文泉驿微米黑:style=Regular\n",
      "/usr/share/fonts/X11/misc/wenquanyi_13px.pcf: WenQuanYi Bitmap Song:style=Regular\n",
      "/usr/share/fonts/truetype/wqy/wqy-zenhei.ttc: WenQuanYi Zen Hei,文泉驛正黑,文泉驿正黑:style=Regular\n",
      "/usr/share/fonts/X11/misc/wenquanyi_12pt.pcf: WenQuanYi Bitmap Song:style=Regular\n",
      "/usr/share/fonts/truetype/wqy/wqy-zenhei.ttc: WenQuanYi Zen Hei Sharp,文泉驛點陣正黑,文泉驿点阵正黑:style=Regular\n",
      "/usr/share/fonts/X11/misc/wenquanyi_10pt.pcf: WenQuanYi Bitmap Song:style=Regular\n",
      "/usr/share/fonts/X11/misc/wenquanyi_9pt.pcf: WenQuanYi Bitmap Song:style=Regular\n",
      "/usr/share/fonts/truetype/droid/DroidSansFallbackFull.ttf: Droid Sans Fallback:style=Regular\n",
      "/usr/share/fonts/X11/misc/wenquanyi_11pt.pcf: WenQuanYi Bitmap Song:style=Regular\n",
      "/usr/share/fonts/truetype/wqy/wqy-zenhei.ttc: WenQuanYi Zen Hei Mono,文泉驛等寬正黑,文泉驿等宽正黑:style=Regular\n",
      "/usr/share/fonts/truetype/wqy/wqy-microhei.ttc: WenQuanYi Micro Hei Mono,文泉驛等寬微米黑,文泉驿等宽微米黑:style=Regular\n",
      "/usr/share/fonts/truetype/msyahei/ms-ya-hei.ttf: Microsoft YaHei,微软雅黑:style=Regular,Normal,obyčejné,Standard,Κανονικά,Normaali,Normál,Normale,Standaard,Normalny,Обычный,Normálne,Navadno,Arrunta\n"
     ]
    }
   ],
   "source": [
    "!fc-list :lang=zh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "#fc-list :lang=zh\n",
    "font_path='/usr/share/fonts/truetype/msyahei/ms-ya-hei.ttf'\n",
    "wordcloud = WordCloud(font_path=font_path, width=1000, height=860,).generate(txt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.5, 999.5, 859.5, -0.5)"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#不支持中文\n",
    "\n",
    "plt.imshow(wordcloud, interpolation='bilinear')\n",
    "plt.axis(\"off\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import font_manager\n",
    "# fname中选择一个你本机查询出来的字体 若没有中文字体则需要你本人手动安装\n",
    "font = font_manager.FontProperties(fname=\"/usr/share/fonts/truetype/msyahei/ms-ya-hei.ttf\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imsave('wuhan.jpg',wordcloud)\n",
    "plt.savefig('wuhan2.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[0;31mSignature:\u001b[0m\n",
       "\u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mimshow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mcmap\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mnorm\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0maspect\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0minterpolation\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0malpha\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mvmin\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mvmax\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0morigin\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mextent\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mshape\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m<\u001b[0m\u001b[0mdeprecated\u001b[0m \u001b[0mparameter\u001b[0m\u001b[0;34m>\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mfilternorm\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mfilterrad\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m4.0\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mimlim\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m<\u001b[0m\u001b[0mdeprecated\u001b[0m \u001b[0mparameter\u001b[0m\u001b[0;34m>\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mresample\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0murl\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0;34m*\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
       "\u001b[0;31mDocstring:\u001b[0m\n",
       "Display an image, i.e. data on a 2D regular raster.\n",
       "\n",
       "Parameters\n",
       "----------\n",
       "X : array-like or PIL image\n",
       "    The image data. Supported array shapes are:\n",
       "\n",
       "    - (M, N): an image with scalar data. The data is visualized\n",
       "      using a colormap.\n",
       "    - (M, N, 3): an image with RGB values (0-1 float or 0-255 int).\n",
       "    - (M, N, 4): an image with RGBA values (0-1 float or 0-255 int),\n",
       "      i.e. including transparency.\n",
       "\n",
       "    The first two dimensions (M, N) define the rows and columns of\n",
       "    the image.\n",
       "\n",
       "    Out-of-range RGB(A) values are clipped.\n",
       "\n",
       "cmap : str or `~matplotlib.colors.Colormap`, optional\n",
       "    The Colormap instance or registered colormap name used to map\n",
       "    scalar data to colors. This parameter is ignored for RGB(A) data.\n",
       "    Defaults to :rc:`image.cmap`.\n",
       "\n",
       "norm : `~matplotlib.colors.Normalize`, optional\n",
       "    The `Normalize` instance used to scale scalar data to the [0, 1]\n",
       "    range before mapping to colors using *cmap*. By default, a linear\n",
       "    scaling mapping the lowest value to 0 and the highest to 1 is used.\n",
       "    This parameter is ignored for RGB(A) data.\n",
       "\n",
       "aspect : {'equal', 'auto'} or float, optional\n",
       "    Controls the aspect ratio of the axes. The aspect is of particular\n",
       "    relevance for images since it may distort the image, i.e. pixel\n",
       "    will not be square.\n",
       "\n",
       "    This parameter is a shortcut for explicitly calling\n",
       "    `.Axes.set_aspect`. See there for further details.\n",
       "\n",
       "    - 'equal': Ensures an aspect ratio of 1. Pixels will be square\n",
       "      (unless pixel sizes are explicitly made non-square in data\n",
       "      coordinates using *extent*).\n",
       "    - 'auto': The axes is kept fixed and the aspect is adjusted so\n",
       "      that the data fit in the axes. In general, this will result in\n",
       "      non-square pixels.\n",
       "\n",
       "    If not given, use :rc:`image.aspect` (default: 'equal').\n",
       "\n",
       "interpolation : str, optional\n",
       "    The interpolation method used. If *None*\n",
       "    :rc:`image.interpolation` is used, which defaults to 'nearest'.\n",
       "\n",
       "    Supported values are 'none', 'nearest', 'bilinear', 'bicubic',\n",
       "    'spline16', 'spline36', 'hanning', 'hamming', 'hermite', 'kaiser',\n",
       "    'quadric', 'catrom', 'gaussian', 'bessel', 'mitchell', 'sinc',\n",
       "    'lanczos'.\n",
       "\n",
       "    If *interpolation* is 'none', then no interpolation is performed\n",
       "    on the Agg, ps, pdf and svg backends. Other backends will fall back\n",
       "    to 'nearest'. Note that most SVG renders perform interpolation at\n",
       "    rendering and that the default interpolation method they implement\n",
       "    may differ.\n",
       "\n",
       "    See\n",
       "    :doc:`/gallery/images_contours_and_fields/interpolation_methods`\n",
       "    for an overview of the supported interpolation methods.\n",
       "\n",
       "    Some interpolation methods require an additional radius parameter,\n",
       "    which can be set by *filterrad*. Additionally, the antigrain image\n",
       "    resize filter is controlled by the parameter *filternorm*.\n",
       "\n",
       "alpha : scalar, optional\n",
       "    The alpha blending value, between 0 (transparent) and 1 (opaque).\n",
       "    This parameter is ignored for RGBA input data.\n",
       "\n",
       "vmin, vmax : scalar, optional\n",
       "    When using scalar data and no explicit *norm*, *vmin* and *vmax*\n",
       "    define the data range that the colormap covers. By default,\n",
       "    the colormap covers the complete value range of the supplied\n",
       "    data. *vmin*, *vmax* are ignored if the *norm* parameter is used.\n",
       "\n",
       "origin : {'upper', 'lower'}, optional\n",
       "    Place the [0,0] index of the array in the upper left or lower left\n",
       "    corner of the axes. The convention 'upper' is typically used for\n",
       "    matrices and images.\n",
       "    If not given, :rc:`image.origin` is used, defaulting to 'upper'.\n",
       "\n",
       "    Note that the vertical axes points upward for 'lower'\n",
       "    but downward for 'upper'.\n",
       "\n",
       "    See the :doc:`/tutorials/intermediate/imshow_extent` tutorial for\n",
       "    examples and a more detailed description.\n",
       "\n",
       "extent : scalars (left, right, bottom, top), optional\n",
       "    The bounding box in data coordinates that the image will fill.\n",
       "    The image is stretched individually along x and y to fill the box.\n",
       "\n",
       "    The default extent is determined by the following conditions.\n",
       "    Pixels have unit size in data coordinates. Their centers are on\n",
       "    integer coordinates, and their center coordinates range from 0 to\n",
       "    columns-1 horizontally and from 0 to rows-1 vertically.\n",
       "\n",
       "    Note that the direction of the vertical axis and thus the default\n",
       "    values for top and bottom depend on *origin*:\n",
       "\n",
       "    - For ``origin == 'upper'`` the default is\n",
       "      ``(-0.5, numcols-0.5, numrows-0.5, -0.5)``.\n",
       "    - For ``origin == 'lower'`` the default is\n",
       "      ``(-0.5, numcols-0.5, -0.5, numrows-0.5)``.\n",
       "\n",
       "    See the :doc:`/tutorials/intermediate/imshow_extent` tutorial for\n",
       "    examples and a more detailed description.\n",
       "\n",
       "filternorm : bool, optional, default: True\n",
       "    A parameter for the antigrain image resize filter (see the\n",
       "    antigrain documentation).  If *filternorm* is set, the filter\n",
       "    normalizes integer values and corrects the rounding errors. It\n",
       "    doesn't do anything with the source floating point values, it\n",
       "    corrects only integers according to the rule of 1.0 which means\n",
       "    that any sum of pixel weights must be equal to 1.0.  So, the\n",
       "    filter function must produce a graph of the proper shape.\n",
       "\n",
       "filterrad : float > 0, optional, default: 4.0\n",
       "    The filter radius for filters that have a radius parameter, i.e.\n",
       "    when interpolation is one of: 'sinc', 'lanczos' or 'blackman'.\n",
       "\n",
       "resample : bool, optional\n",
       "    When *True*, use a full resampling method.  When *False*, only\n",
       "    resample when the output image is larger than the input image.\n",
       "\n",
       "url : str, optional\n",
       "    Set the url of the created `.AxesImage`. See `.Artist.set_url`.\n",
       "\n",
       "Returns\n",
       "-------\n",
       "image : `~matplotlib.image.AxesImage`\n",
       "\n",
       "Other Parameters\n",
       "----------------\n",
       "**kwargs : `~matplotlib.artist.Artist` properties\n",
       "    These parameters are passed on to the constructor of the\n",
       "    `.AxesImage` artist.\n",
       "\n",
       "See also\n",
       "--------\n",
       "matshow : Plot a matrix or an array as an image.\n",
       "\n",
       "Notes\n",
       "-----\n",
       "Unless *extent* is used, pixel centers will be located at integer\n",
       "coordinates. In other words: the origin will coincide with the center\n",
       "of pixel (0, 0).\n",
       "\n",
       "There are two common representations for RGB images with an alpha\n",
       "channel:\n",
       "\n",
       "-   Straight (unassociated) alpha: R, G, and B channels represent the\n",
       "    color of the pixel, disregarding its opacity.\n",
       "-   Premultiplied (associated) alpha: R, G, and B channels represent\n",
       "    the color of the pixel, adjusted for its opacity by multiplication.\n",
       "\n",
       "`~matplotlib.pyplot.imshow` expects RGB images adopting the straight\n",
       "(unassociated) alpha representation.\n",
       "\n",
       ".. note::\n",
       "    In addition to the above described arguments, this function can take a\n",
       "    **data** keyword argument. If such a **data** argument is given, the\n",
       "    following arguments are replaced by **data[<arg>]**:\n",
       "\n",
       "    * All positional and all keyword arguments.\n",
       "\n",
       "    Objects passed as **data** must support item access (``data[<arg>]``) and\n",
       "    membership test (``<arg> in data``).\n",
       "\u001b[0;31mFile:\u001b[0m      /usr/local/lib/python3.7/dist-packages/matplotlib/pyplot.py\n",
       "\u001b[0;31mType:\u001b[0m      function\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['红十字会',\n",
       " '探访',\n",
       " '武汉市',\n",
       " '东西',\n",
       " '那么',\n",
       " '怎么',\n",
       " '记者',\n",
       " '抽调',\n",
       " '私下',\n",
       " '工作人员',\n",
       " '人员',\n",
       " '一位',\n",
       " '部门',\n",
       " '其他',\n",
       " '红十字会',\n",
       " '探访',\n",
       " '武汉市',\n",
       " '东西',\n",
       " '那么',\n",
       " '怎么',\n",
       " '记者',\n",
       " '武汉市',\n",
       " '央广',\n",
       " '31',\n",
       " '打大仗',\n",
       " '总台',\n",
       " '红十字会',\n",
       " '探访',\n",
       " '记者',\n",
       " '详情',\n",
       " '湖北省',\n",
       " '打仗',\n",
       " '胜利',\n",
       " '有点',\n",
       " '来到',\n",
       " '位于',\n",
       " '东西',\n",
       " '那么',\n",
       " '怎么',\n",
       " '湖北省委',\n",
       " '直播',\n",
       " '书记',\n",
       " '战疫',\n",
       " '岩松',\n",
       " '马国强',\n",
       " '白岩松',\n",
       " '关注',\n",
       " '连线',\n",
       " '独家',\n",
       " '疫情',\n",
       " '市委书记',\n",
       " '对话',\n",
       " '今晚',\n",
       " '武汉',\n",
       " '新闻',\n",
       " '共同',\n",
       " '一起',\n",
       " '继续',\n",
       " '微博',\n",
       " '直播',\n",
       " '央视',\n",
       " '新闻',\n",
       " '武汉协和医院',\n",
       " '物资',\n",
       " '急需',\n",
       " '医疗',\n",
       " '20',\n",
       " '沈文敏',\n",
       " '外罩',\n",
       " '今天下午',\n",
       " '口罩',\n",
       " '手套',\n",
       " '万个',\n",
       " '护士',\n",
       " '防护',\n",
       " '一线',\n",
       " '尽快',\n",
       " '送到',\n",
       " '收到',\n",
       " '到达',\n",
       " '一批',\n",
       " '医生',\n",
       " '武汉',\n",
       " '小姐姐',\n",
       " '800',\n",
       " '发微博',\n",
       " 'icon',\n",
       " '为武',\n",
       " '医院',\n",
       " '盒饭',\n",
       " '盘龙城',\n",
       " '昵称',\n",
       " '医护人员',\n",
       " '点亮',\n",
       " '日记',\n",
       " '餐厅',\n",
       " '受不了',\n",
       " '做饭',\n",
       " '金银',\n",
       " '话题',\n",
       " '事儿',\n",
       " '专门',\n",
       " '武汉',\n",
       " '小姐姐',\n",
       " '800',\n",
       " '单泽',\n",
       " 'vlog',\n",
       " '盘龙城',\n",
       " '餐厅',\n",
       " '央视',\n",
       " '做饭',\n",
       " '医院',\n",
       " '每天',\n",
       " '一家',\n",
       " '记者',\n",
       " '微博',\n",
       " '央视',\n",
       " '视频',\n",
       " '新闻',\n",
       " '环卫',\n",
       " '急转',\n",
       " '纸条',\n",
       " '日照',\n",
       " '武汉',\n",
       " '大众网',\n",
       " '白衣天使',\n",
       " '12000',\n",
       " '31',\n",
       " '东港',\n",
       " '留言',\n",
       " '加油',\n",
       " '头戴',\n",
       " '心意',\n",
       " '派出所',\n",
       " '大爷',\n",
       " '帽子',\n",
       " '转身',\n",
       " '一张',\n",
       " '山东',\n",
       " '环卫',\n",
       " '大众网',\n",
       " '12000',\n",
       " '东港',\n",
       " '急转',\n",
       " '留言',\n",
       " '纸条',\n",
       " '日照',\n",
       " '派出所',\n",
       " '大爷',\n",
       " '转身',\n",
       " '微博',\n",
       " '人民日报',\n",
       " '视频',\n",
       " '校友会',\n",
       " '北加州',\n",
       " '医用',\n",
       " '华科',\n",
       " '2.5',\n",
       " '20',\n",
       " '2.75',\n",
       " '4000',\n",
       " '武汉协和医院',\n",
       " '防护服',\n",
       " '口罩',\n",
       " '武大',\n",
       " '手套',\n",
       " '好消息',\n",
       " '捐赠',\n",
       " '汇报',\n",
       " '总算',\n",
       " '紧急',\n",
       " '医疗',\n",
       " '一批',\n",
       " '武汉',\n",
       " '医护',\n",
       " '关爱',\n",
       " '肺炎',\n",
       " '抗击',\n",
       " '31',\n",
       " '21',\n",
       " '10',\n",
       " '李文亮',\n",
       " '守护者',\n",
       " '第一笔',\n",
       " '后盾',\n",
       " '拨付',\n",
       " '肺炎',\n",
       " '基金会',\n",
       " '病毒',\n",
       " '防范',\n",
       " '试图',\n",
       " '客观',\n",
       " '新型',\n",
       " '提前',\n",
       " '贡献',\n",
       " '行动',\n",
       " '特征',\n",
       " '明确',\n",
       " '医护',\n",
       " '关爱',\n",
       " '肺炎',\n",
       " '抗击',\n",
       " '后盾',\n",
       " '守护者',\n",
       " '医护',\n",
       " '31',\n",
       " '行动',\n",
       " '疫情',\n",
       " '一线',\n",
       " '项目',\n",
       " '公益',\n",
       " '网友',\n",
       " '转自',\n",
       " '武汉协和医院',\n",
       " '某会',\n",
       " '惹怒',\n",
       " '置之不理',\n",
       " '医护人员',\n",
       " '求助',\n",
       " '捐赠',\n",
       " '绕过',\n",
       " '病毒',\n",
       " '聚集',\n",
       " '据说',\n",
       " '工作人员',\n",
       " '危险',\n",
       " '网上',\n",
       " '身上',\n",
       " '它们',\n",
       " '直接',\n",
       " '工作',\n",
       " '转自',\n",
       " '武汉协和医院',\n",
       " '置之不理',\n",
       " '医护人员',\n",
       " '绕过',\n",
       " '据说',\n",
       " '工作人员',\n",
       " '网友',\n",
       " '因为',\n",
       " '黎黎',\n",
       " 'Lily',\n",
       " '微博',\n",
       " '视频',\n",
       " '胡亚波',\n",
       " '总台',\n",
       " '红十字',\n",
       " '展馆',\n",
       " '红十字会',\n",
       " '探访',\n",
       " '东西',\n",
       " '征用',\n",
       " '紧缺',\n",
       " '武汉市',\n",
       " '记者',\n",
       " '民用',\n",
       " '捐赠',\n",
       " '有用',\n",
       " '物资',\n",
       " '武汉',\n",
       " '市长',\n",
       " '一方面',\n",
       " '临时',\n",
       " '原来',\n",
       " '总台',\n",
       " '红十字会',\n",
       " '探访',\n",
       " '东西',\n",
       " '那么',\n",
       " '怎么',\n",
       " '武汉',\n",
       " '记者',\n",
       " '总台',\n",
       " '红十字会',\n",
       " '探访',\n",
       " '武汉市',\n",
       " '记者',\n",
       " '医院',\n",
       " '分三六',\n",
       " '物资',\n",
       " '工作人员',\n",
       " '天佑',\n",
       " '红十字会',\n",
       " '救命',\n",
       " '看病',\n",
       " '捐赠',\n",
       " '宏观调控',\n",
       " '回应',\n",
       " '等级',\n",
       " '什么',\n",
       " '湖北',\n",
       " '中华人民共和国',\n",
       " '分配',\n",
       " '群众',\n",
       " '这位',\n",
       " '人民',\n",
       " '表示',\n",
       " '分三六',\n",
       " '红十字会',\n",
       " '拟定',\n",
       " '回应',\n",
       " '物资',\n",
       " '自行',\n",
       " '湖北',\n",
       " '工作人员',\n",
       " '分配',\n",
       " '医院',\n",
       " '什么',\n",
       " '安贞',\n",
       " '西里',\n",
       " '北京',\n",
       " '安贞',\n",
       " '西里',\n",
       " '北京',\n",
       " '冠状病毒',\n",
       " '新型',\n",
       " '药物',\n",
       " '肺炎',\n",
       " '感染',\n",
       " '蒋华良',\n",
       " '口服液',\n",
       " '可抑制',\n",
       " '攻关',\n",
       " '双黄连',\n",
       " '中成药',\n",
       " '上海',\n",
       " '牵头',\n",
       " '应急',\n",
       " '病毒',\n",
       " '院士',\n",
       " '团队',\n",
       " '武汉',\n",
       " '启动',\n",
       " '此前',\n",
       " '冠状病毒',\n",
       " '董瑞丰',\n",
       " '同济',\n",
       " '肺炎',\n",
       " '附属',\n",
       " '病毒',\n",
       " '临床',\n",
       " '新型',\n",
       " '感染',\n",
       " '武汉',\n",
       " '药物',\n",
       " '开展',\n",
       " '医院',\n",
       " '大学',\n",
       " '联合',\n",
       " '上海',\n",
       " '发现',\n",
       " '研究',\n",
       " '记者',\n",
       " '医用',\n",
       " '防护眼镜',\n",
       " '新空',\n",
       " '429',\n",
       " '武汉协和医院',\n",
       " '防护服',\n",
       " '直飞',\n",
       " '萧山',\n",
       " '协和',\n",
       " '口罩',\n",
       " '装满',\n",
       " '运载',\n",
       " '降落',\n",
       " '贝尔',\n",
       " '隶属于',\n",
       " '起飞',\n",
       " '一架',\n",
       " '通航',\n",
       " '直升机',\n",
       " '今晚',\n",
       " '新空',\n",
       " '429',\n",
       " '萧山',\n",
       " '加油',\n",
       " '贝尔',\n",
       " '隶属于',\n",
       " '一架',\n",
       " '通航',\n",
       " '直升机',\n",
       " '今晚',\n",
       " '杭州',\n",
       " '计划',\n",
       " '之间',\n",
       " '水族馆',\n",
       " '生物',\n",
       " '物语',\n",
       " '航空',\n",
       " '药物',\n",
       " '冠状病毒',\n",
       " '新型',\n",
       " '31',\n",
       " 'SARS',\n",
       " '可抑制',\n",
       " '攻关',\n",
       " '双黄连',\n",
       " '上海',\n",
       " '肺炎',\n",
       " '发现',\n",
       " '研究',\n",
       " '应急',\n",
       " '中国科学院',\n",
       " '病毒',\n",
       " '团队',\n",
       " '获悉',\n",
       " '感染',\n",
       " '武汉',\n",
       " '前期',\n",
       " '华中科技大学',\n",
       " '冠状',\n",
       " '可抑制',\n",
       " '同济',\n",
       " '双黄连',\n",
       " '附属',\n",
       " '病毒',\n",
       " '新华社',\n",
       " '临床',\n",
       " '新型',\n",
       " '武汉',\n",
       " '药物',\n",
       " '开展',\n",
       " '医院',\n",
       " '联合',\n",
       " '上海',\n",
       " '发现',\n",
       " '研究',\n",
       " '火神',\n",
       " '医院',\n",
       " '神山',\n",
       " '冠状病毒',\n",
       " '收治病人',\n",
       " '3.4',\n",
       " '肺炎',\n",
       " '建筑面积',\n",
       " '全力',\n",
       " '万平方米',\n",
       " '新型',\n",
       " '最新',\n",
       " '推进',\n",
       " '介绍',\n",
       " '正式',\n",
       " '分别',\n",
       " '正在',\n",
       " '情况',\n",
       " '目前',\n",
       " '冠状病毒',\n",
       " '肺炎',\n",
       " '疫情',\n",
       " '新型',\n",
       " '医院',\n",
       " '神山',\n",
       " '火神',\n",
       " '实时',\n",
       " '地图',\n",
       " '更新',\n",
       " '最新',\n",
       " '全国',\n",
       " '分别',\n",
       " '情况',\n",
       " '不该',\n",
       " '公众',\n",
       " '新冠',\n",
       " '武汉协和医院',\n",
       " '3000',\n",
       " '领走',\n",
       " '定点医院',\n",
       " '红十字会',\n",
       " '医护人员',\n",
       " '口罩',\n",
       " '肺炎',\n",
       " '列出',\n",
       " '日夜',\n",
       " '强迫',\n",
       " '防护',\n",
       " '舆论',\n",
       " '透明',\n",
       " '落实',\n",
       " '一线',\n",
       " '湖北',\n",
       " '不该',\n",
       " '公众',\n",
       " '##',\n",
       " '红十字会',\n",
       " '拨付',\n",
       " '口罩',\n",
       " '强迫',\n",
       " '第一批',\n",
       " '舆论',\n",
       " '透明',\n",
       " '落实',\n",
       " '湖北',\n",
       " '执行',\n",
       " '信息',\n",
       " '使用',\n",
       " '亿元',\n",
       " '资金',\n",
       " '情况',\n",
       " '红十字会',\n",
       " '慈善',\n",
       " '总会',\n",
       " '武汉',\n",
       " '物资供应',\n",
       " '菜农',\n",
       " '监工',\n",
       " '寿光',\n",
       " '亿多',\n",
       " '拨付',\n",
       " '捐款',\n",
       " '捐赠',\n",
       " '湖北省',\n",
       " '连夜',\n",
       " '回应',\n",
       " '定向',\n",
       " '质疑',\n",
       " '收到',\n",
       " '网友',\n",
       " '监督',\n",
       " '万余名',\n",
       " '物资供应',\n",
       " '监工',\n",
       " '医务',\n",
       " '红十字会',\n",
       " '求助',\n",
       " '奋战',\n",
       " '工作者',\n",
       " '湖北省',\n",
       " '回应',\n",
       " '武汉',\n",
       " '监督',\n",
       " '网络',\n",
       " '医院',\n",
       " '大家',\n",
       " '看到',\n",
       " '问题',\n",
       " '火神',\n",
       " '医院',\n",
       " '收治',\n",
       " '监工',\n",
       " '神山',\n",
       " '直播',\n",
       " '武汉市',\n",
       " '用来',\n",
       " '近日',\n",
       " '集中',\n",
       " '建设',\n",
       " '一起',\n",
       " '决定',\n",
       " '直播',\n",
       " '直击',\n",
       " '火神',\n",
       " '京报',\n",
       " '全天候',\n",
       " '加油',\n",
       " '武汉',\n",
       " '发起',\n",
       " '医院',\n",
       " '建设',\n",
       " '一起',\n",
       " '微博',\n",
       " '京报',\n",
       " '直播',\n",
       " '出院',\n",
       " '20',\n",
       " '金银',\n",
       " '武汉市',\n",
       " '医院',\n",
       " '患者',\n",
       " '冠状病毒',\n",
       " '72',\n",
       " '今天下午',\n",
       " '数最多',\n",
       " '肺炎',\n",
       " '确诊',\n",
       " '之声',\n",
       " '新型',\n",
       " '武汉',\n",
       " '湖北',\n",
       " '集体',\n",
       " '共有',\n",
       " '累计',\n",
       " '截至',\n",
       " '##',\n",
       " '投稿',\n",
       " '医护人员',\n",
       " '武汉市',\n",
       " '捐赠',\n",
       " '慈善',\n",
       " '疫情',\n",
       " '总会',\n",
       " '防护',\n",
       " '物资',\n",
       " '地图',\n",
       " '制作',\n",
       " '最新',\n",
       " '装备',\n",
       " '公告',\n",
       " '才能',\n",
       " '使用',\n",
       " '时候',\n",
       " '情况',\n",
       " '开始',\n",
       " '宋彩萍',\n",
       " '博拉',\n",
       " '武汉',\n",
       " '妈妈',\n",
       " '2015',\n",
       " '儿子',\n",
       " '再战',\n",
       " '军医',\n",
       " '驰援',\n",
       " '奔赴',\n",
       " '加油',\n",
       " '拥抱',\n",
       " '大大的',\n",
       " '出征',\n",
       " '抗击',\n",
       " '归来',\n",
       " '高出',\n",
       " '迎接',\n",
       " '一头',\n",
       " '湖北',\n",
       " '红十字会',\n",
       " '探访',\n",
       " '武汉市',\n",
       " '东西',\n",
       " '那么',\n",
       " '怎么',\n",
       " '记者',\n",
       " '红十字会',\n",
       " '工作人员',\n",
       " '武汉市',\n",
       " '记者',\n",
       " '现场',\n",
       " '央广',\n",
       " '31',\n",
       " '162',\n",
       " '总台',\n",
       " '抽调',\n",
       " '防备',\n",
       " '私下',\n",
       " '湖北省',\n",
       " '舆论',\n",
       " '感受',\n",
       " '焦点',\n",
       " '始终',\n",
       " '胜利',\n",
       " '采访',\n",
       " '见到',\n",
       " '红十字会',\n",
       " '探访',\n",
       " '武汉市',\n",
       " '东西',\n",
       " '那么',\n",
       " '怎么',\n",
       " '记者',\n",
       " '红十字会',\n",
       " '武汉市',\n",
       " '工作人员',\n",
       " '记者',\n",
       " '现场',\n",
       " '央广',\n",
       " '31',\n",
       " '162',\n",
       " '打大仗',\n",
       " '总台',\n",
       " '探访',\n",
       " '抽调',\n",
       " '详情',\n",
       " '防备',\n",
       " '私下',\n",
       " '湖北省',\n",
       " '舆论',\n",
       " '打仗',\n",
       " '几十年',\n",
       " '感受',\n",
       " '湖北省委',\n",
       " '直播',\n",
       " '书记',\n",
       " '战疫',\n",
       " '岩松',\n",
       " '马国强',\n",
       " '白岩松',\n",
       " '关注',\n",
       " '连线',\n",
       " '独家',\n",
       " '疫情',\n",
       " '市委书记',\n",
       " '对话',\n",
       " '今晚',\n",
       " '武汉',\n",
       " '新闻',\n",
       " '共同',\n",
       " '一起',\n",
       " '继续',\n",
       " '微博',\n",
       " '直播',\n",
       " '央视',\n",
       " '新闻',\n",
       " '物资',\n",
       " '武汉协和医院',\n",
       " '急需',\n",
       " '校友会',\n",
       " '医疗',\n",
       " '这批',\n",
       " '华科',\n",
       " '20',\n",
       " '沈文敏',\n",
       " '外罩',\n",
       " '今天下午',\n",
       " '口罩',\n",
       " '武大',\n",
       " '手套',\n",
       " '捐赠',\n",
       " '万个',\n",
       " '护士',\n",
       " '防护',\n",
       " '一线',\n",
       " '尽快',\n",
       " '小姐姐',\n",
       " '800',\n",
       " '盒饭',\n",
       " '武汉',\n",
       " '医护人员',\n",
       " '朋友圈',\n",
       " '1000',\n",
       " '发微博',\n",
       " 'icon',\n",
       " '为武',\n",
       " '医院',\n",
       " '每天',\n",
       " '盘龙城',\n",
       " '昵称',\n",
       " '忙不过来',\n",
       " '上阵',\n",
       " '点亮',\n",
       " '兄妹',\n",
       " '店主',\n",
       " '日记',\n",
       " '小姐姐',\n",
       " '武汉',\n",
       " '800',\n",
       " '盒饭',\n",
       " '医护人员',\n",
       " '朋友圈',\n",
       " '1000',\n",
       " '发微博',\n",
       " 'icon',\n",
       " '张竣',\n",
       " '医院',\n",
       " '每天',\n",
       " '盘龙城',\n",
       " '昵称',\n",
       " '总台',\n",
       " '忙不过来',\n",
       " '上阵',\n",
       " '点亮',\n",
       " '兄妹',\n",
       " '店主',\n",
       " '单泽',\n",
       " 'vlog',\n",
       " '央视',\n",
       " '武汉',\n",
       " '记者',\n",
       " '微博',\n",
       " '央视',\n",
       " '视频',\n",
       " '新闻',\n",
       " '环卫',\n",
       " '派出所',\n",
       " '东港',\n",
       " '急转',\n",
       " '纸包',\n",
       " '纸条',\n",
       " '日照',\n",
       " '大爷',\n",
       " '武汉',\n",
       " '大众网',\n",
       " '转身',\n",
       " '白衣天使',\n",
       " '12000',\n",
       " '31',\n",
       " '公安分局',\n",
       " '留言',\n",
       " '千元',\n",
       " '加油',\n",
       " '头戴',\n",
       " '心意',\n",
       " '环卫',\n",
       " '派出所',\n",
       " '东港',\n",
       " '急转',\n",
       " '纸包',\n",
       " '纸条',\n",
       " '日照',\n",
       " '大爷',\n",
       " '武汉',\n",
       " '大众网',\n",
       " '转身',\n",
       " '白衣天使',\n",
       " '12000',\n",
       " '31',\n",
       " '公安分局',\n",
       " '留言',\n",
       " '千元',\n",
       " '加油',\n",
       " '头戴',\n",
       " '心意',\n",
       " '微博',\n",
       " '人民日报',\n",
       " '视频',\n",
       " '校友会',\n",
       " '北加州',\n",
       " '医用',\n",
       " '华科',\n",
       " '2.5',\n",
       " '20',\n",
       " '2.75',\n",
       " '4000',\n",
       " '武汉协和医院',\n",
       " '防护服',\n",
       " '口罩',\n",
       " '武大',\n",
       " '手套',\n",
       " '好消息',\n",
       " '捐赠',\n",
       " '汇报',\n",
       " '总算',\n",
       " '紧急',\n",
       " '医疗',\n",
       " '一批',\n",
       " '武汉',\n",
       " '医护',\n",
       " '关爱',\n",
       " '肺炎',\n",
       " '抗击',\n",
       " '李文亮',\n",
       " '31',\n",
       " '21',\n",
       " '10',\n",
       " '守护者',\n",
       " '受益人',\n",
       " '支持',\n",
       " '第一笔',\n",
       " '中心医院',\n",
       " '后盾',\n",
       " '拨付',\n",
       " '武汉市',\n",
       " '肺炎',\n",
       " '基金会',\n",
       " '款项',\n",
       " '真相',\n",
       " '敢于',\n",
       " '病毒',\n",
       " '防范',\n",
       " '试图',\n",
       " '10',\n",
       " '医护',\n",
       " '关爱',\n",
       " '肺炎',\n",
       " '抗击',\n",
       " '李文亮',\n",
       " '氧气管',\n",
       " '工作',\n",
       " '31',\n",
       " '21',\n",
       " '10',\n",
       " '疾控',\n",
       " '守护者',\n",
       " '打字',\n",
       " '接诊',\n",
       " '受益人',\n",
       " '训诫',\n",
       " '支持',\n",
       " '第一笔',\n",
       " '中心医院',\n",
       " '获知',\n",
       " '广泛传播',\n",
       " '后盾',\n",
       " '拨付',\n",
       " '疑似',\n",
       " '曾光',\n",
       " '忧国忧民',\n",
       " '应该',\n",
       " '赞扬',\n",
       " '见解',\n",
       " '保护',\n",
       " '一定',\n",
       " '他们',\n",
       " '医护',\n",
       " '后盾',\n",
       " '守护者',\n",
       " '资助',\n",
       " '找寻到',\n",
       " '15',\n",
       " '共克',\n",
       " '行动',\n",
       " '时艰',\n",
       " '肺炎',\n",
       " '加油',\n",
       " '检疫',\n",
       " '基金会',\n",
       " '疫情',\n",
       " '护士',\n",
       " '坚实',\n",
       " '抗击',\n",
       " '一线',\n",
       " '程序',\n",
       " '医生',\n",
       " '公益',\n",
       " '11',\n",
       " '协和',\n",
       " '网友',\n",
       " '领用',\n",
       " '转自',\n",
       " '武汉协和医院',\n",
       " '某会',\n",
       " '惹怒',\n",
       " '我们',\n",
       " '置之不理',\n",
       " '医护人员',\n",
       " '求助',\n",
       " '要饭',\n",
       " '排在',\n",
       " '捐赠',\n",
       " '绕过',\n",
       " '病毒',\n",
       " '物资',\n",
       " '聚集',\n",
       " '据说',\n",
       " '工作人员',\n",
       " '12',\n",
       " '协和',\n",
       " '网友',\n",
       " '领用',\n",
       " '转自',\n",
       " '武汉协和医院',\n",
       " '某会',\n",
       " '惹怒',\n",
       " '我们',\n",
       " '置之不理',\n",
       " '医护人员',\n",
       " '求助',\n",
       " '要饭',\n",
       " '排在',\n",
       " '捐赠',\n",
       " '绕过',\n",
       " '病毒',\n",
       " '物资',\n",
       " '聚集',\n",
       " '据说',\n",
       " '工作人员',\n",
       " '黎黎',\n",
       " 'Lily',\n",
       " '微博',\n",
       " '视频',\n",
       " '13',\n",
       " '展馆',\n",
       " '红十字会',\n",
       " '武汉市',\n",
       " '捐赠',\n",
       " '物资',\n",
       " '胡亚波',\n",
       " '总台',\n",
       " '造册',\n",
       " '探访',\n",
       " '东西',\n",
       " '征用',\n",
       " '堆放',\n",
       " '紧缺',\n",
       " '常务副',\n",
       " '记者',\n",
       " '民用',\n",
       " '存放',\n",
       " '角落',\n",
       " '仓库',\n",
       " '有用',\n",
       " '14',\n",
       " '展馆',\n",
       " '红十字会',\n",
       " '东西',\n",
       " '武汉市',\n",
       " '捐赠',\n",
       " '物资',\n",
       " '胡亚波',\n",
       " '总台',\n",
       " '进不来',\n",
       " '造册',\n",
       " '探访',\n",
       " '堆积如山',\n",
       " '医护人员',\n",
       " '征用',\n",
       " '堆放',\n",
       " '紧缺',\n",
       " '常务副',\n",
       " '需要',\n",
       " '记者',\n",
       " '详情',\n",
       " '东西',\n",
       " ...]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
